Title :
Neural net simulation: SFSN model for image compression
Author_Institution :
Dept. of Comput. Sci., New Mexico Tech., NM, USA
Abstract :
We present a recent simulation of our neural net model for image compression (SFSN) which is based on the Kohonen SOFM system. Our previous work was limited to a certain scope of image domains. Our updated simulator is meant to be very general via a well-constructed universal codebook for each domain of images. It shows an improvement over the traditional peer non-neural models (e.g., wavelet and JPEG) in some image domains. We present our neural compression simulator and our most recent results in some important domains, such as satellite and document imaging
Keywords :
data compression; digital simulation; document image processing; image coding; remote sensing; self-organising feature maps; Kohonen SOFM; SFSN model; document imaging; image compression; neural compression simulator; neural net simulation; satellite imaging; universal codebook; Biological system modeling; Computational modeling; Computer science; Convergence; Engines; Image coding; Image storage; Neural networks; Satellites; Transform coding;
Conference_Titel :
Simulation Symposium, 2001. Proceedings. 34th Annual
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1092-2
DOI :
10.1109/SIMSYM.2001.922148